Dark Web OSINT With Python Part Three: Visualization

Welcome back! In this series of blog posts we are wrapping the awesome OnionScan tool and then analyzing the data that falls out of it. If you haven’t read parts one and two in this series then you should go do that first. In this post we are going to analyze our data in a new light by visualizing how hidden services are linked together as well as how hidden services are linked to clearnet sites.

One of the awesome things that OnionScan does is look for links between hidden services and clearnet sites and makes these links available to us in the JSON output. Additionally it looks for IP address leaks or references to IP addresses that could be used for deanonymization.

We are going to extract these connections and create visualizations that will assist us in looking at interesting connections, popular hidden services with a high number of links and along the way learn some Python and how to use Gephi, a visualization tool. Let’s get started!

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Jason tops off this great series on OnionScan by teaching the rudiments of using Gephi to visualize and explore the resulting data.

Can you map yourself from the Dark Web to visible site?

If so, you aren’t hidden well enough.

This entry was posted
on Thursday, September 1st, 2016 at 4:40 pm and is filed under Dark Web, Open Source Intelligence, Python, Tor.
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